Search Results for author:
Found 18 papers, 7 papers with code
MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAM
It can provide robust camera tracking in dynamic environments and at the same time, continuously estimate geometric, semantic, and motion properties for arbitrary objects in the scene.
Pre-training A Neural Language Model Improves The Sample Efficiency of an Emergency Room Classification Model
To build a French national electronic injury surveillance system based on emergency room visits, we aim to develop a coding system to classify their causes from clinical notes in free-text.
Deep Probabilistic Feature-metric Tracking
Dense image alignment from RGB-D images remains a critical issue for real-world applications, especially under challenging lighting conditions and in a wide baseline setting.
A Benchmarking on Cloud based Speech-To-Text Services for French Speech and Background Noise Effect
This study presents a large scale benchmarking on cloud based Speech-To-Text systems: {Google Cloud Speech-To-Text}, {Microsoft Azure Cognitive Services}, {Amazon Transcribe}, {IBM Watson Speech to Text}.
Improving Patent Mining and Relevance Classification using Transformers
Patent analysis and mining are time-consuming and costly processes for companies, but nevertheless essential if they are willing to remain competitive.
Identity-Disentangled Neural Deformation Model for Dynamic Meshes
When applied to dynamically deforming shapes such as the human hands, however, they would need to preserve temporal coherence of the deformation as well as the intrinsic identity of the subject.
Towards a Data-Driven Requirements Engineering Approach: Automatic Analysis of User Reviews
We are concerned by Data Driven Requirements Engineering, and in particular the consideration of user's reviews.
Visual-Inertial Multi-Instance Dynamic SLAM with Object-level Relocalisation
In this paper, we present a tightly-coupled visual-inertial object-level multi-instance dynamic SLAM system.
Learning to Complete Object Shapes for Object-level Mapping in Dynamic Scenes
In this paper, we propose a novel object-level mapping system that can simultaneously segment, track, and reconstruct objects in dynamic scenes.
Mental arithmetic task classification with convolutional neural network based on spectral-temporal features from EEG
We compared this models to three other neural network models with different depths applied to a mental arithmetic task using eye-closed state adapted for patients suffering from motor disorders and a decline in visual functions.
An automated pipeline to create an atlas of in situ hybridization gene expression data in the adult marmoset brain
We present the first automated pipeline to create an atlas of in situ hybridization gene expression in the adult marmoset brain in the same stereotaxic space.
Incremental Dense Reconstruction from Monocular Video with Guided Sparse Feature Volume Fusion
Incrementally recovering 3D dense structures from monocular videos is of paramount importance since it enables various robotics and AR applications.
Boosting GUI Prototyping with Diffusion Models
GUI (graphical user interface) prototyping is a widely-used technique in requirements engineering for gathering and refining requirements, reducing development risks and increasing stakeholder engagement.
Accurate and Interactive Visual-Inertial Sensor Calibration with Next-Best-View and Next-Best-Trajectory Suggestion
Visual-Inertial (VI) sensors are popular in robotics, self-driving vehicles, and augmented and virtual reality applications.
Using Shallow Neural Networks with Functional Connectivity from EEG signals for Early Diagnosis of Alzheimer's and Frontotemporal Dementia
We compare three supervised machine learning techniques to the CNN models to classify EEG signals of AD / FTD and control cases.
Zero-shot Bilingual App Reviews Mining with Large Language Models
App reviews from app stores are crucial for improving software requirements.
NeRF-VO: Real-Time Sparse Visual Odometry with Neural Radiance Fields
We introduce a novel monocular visual odometry (VO) system, NeRF-VO, that integrates learning-based sparse visual odometry for low-latency camera tracking and a neural radiance scene representation for sophisticated dense reconstruction and novel view synthesis.
FuncGrasp: Learning Object-Centric Neural Grasp Functions from Single Annotated Example Object
We present FuncGrasp, a framework that can infer dense yet reliable grasp configurations for unseen objects using one annotated object and single-view RGB-D observation via categorical priors.
